axopy 0.2.3

Documentation: https://axopy.readthedocs.io

Axo-Pythonic synapses are those in which an axon synapses upon a Python program. AxoPy aims to facilitate such connections between electrophysiolgical signals and machines by making it easy for researchers to develop human-computer interface experiments. If you’ve ever found yourself spending more time thinking about how to implement your experiments than thinking about what the experiment should be, AxoPy may be able to help.

AxoPy consists of:

Graphical interface

Central to AxoPy is the graphical user interface providing visual feedback to the subject and controlling the flow of the experiment. The GUI is backed by PyQt5, and you’re free to implement customized graphical elements if those built in to AxoPy don’t suit your needs.

Data acquisition

AxoPy establishes a fairly simple API for communicating with input hardware, so all that’s usually needed is a bit of middleware to get going. Check out pytrigno or pymcc to see what this is like. A couple input devices are built in (keyboard, noise generator), so examples run without needing special hardware.

Data storage

Data is stored in a file structure with common file formats (CSV and HDF5) so you can a) start working with data as soon as an experiment session is over and b) you don’t need anything but standard tools (pandas, h5py) to do so. A high-level interface to the storage structure is also provided to make traversing a dataset simple.

Pipeline processing

Estimating intentions of the user from raw electrophysiological signals often involves a large number of processing operations. AxoPy facilitates flexible construction of pipelines that can be reused in different parts of an experiment and re-used for offline post-processing, etc.

$ pip install axopy

$ conda install -c conda-forge axopy

import axopy

daq = axopy.daq.NoiseGenerator(rate=1000, num_channels=4, read_size=100)
exp = axopy.experiment.Experiment(daq=daq)
exp.run(axopy.task.Oscilloscope())